Machine Learning-Based Badminton Basic Technique Training Model

Badminton is a sport that requires high technical skills. Training in basic badminton techniques is an important first step for players to develop their abilities. However, effective and efficient training methods are often challenges for coaches and players. In this case, the use of machine learning technology can be an innovative solution to increase the effectiveness of basic badminton technique training. This research aims to develop a machine learning-based basic badminton technique training model that can help players improve their skills in a more targeted and personalized way. This research method uses the R & D (Research and Development) research method. The results of this research state that the machine learning-based basic badminton technique training model developed shows effectiveness in improving the technical skills of badminton players. By leveraging personalized training data and tailored feedback, players can identify areas for improvement and refine their technique more efficiently. The conclusion of this research is to produce an innovative and effective basic badminton technique training model based on machine learning. It is hoped that the use of this technology can help badminton coaches and players improve the quality of their training and overall performance. Thus, the implementation of this model has the potential to have a positive impact on the development of badminton skills at both individual and team levels.